Companies × risks
Applied Materials
Applied Materials develops specialised deep learning networks and ML algorithms trained on semiconductor fabrication data for defect detection, classification, and process optimisation, embedded in its manufacturing equipment. Its AI models are proprietary and domain-specific to semiconductor manufacturing.
We reviewed 2 public documents from Applied Materials and found it acknowledges 3 of 24 AI risks, including environmental harm and fraud & scams.
Sector: Agriculture, Mining, Construction and Manufacturing; Other Agriculture, Mining, Construction and Manufacturing
Roles: AI infrastructure provider; Specialized AI developer
AI risks Applied Materials acknowledges
- Environmental harm: “technologies like AI and edge computing offer unprecedented possibilities, but leveraging them responsibly means dealing first with their power consumption. With current technology, today’s datacenters consume about 2% of the world’s electricity - a figure that could jump to 15% by 2025” (2019 Sustainability Report)
- Fraud & scams: “Artificial intelligence and deepfake technologies could be used to attack information systems by creating more effective phishing emails or social engineering and by exploiting vulnerabilities in electronic security programs utilizing false image or voice recognition.” (Applied Materials 2024 Annual Report)
- Devaluation of human creativity: “The use of artificial intelligence in the development of our products and services could also cause loss of intellectual property, as well as subject us to risks related to intellectual property infringement or misappropriation” (Applied Materials 2024 Annual Report)
Documents we reviewed
- 2019 Sustainability Report (ESG report, 2020)
- Applied Materials 2024 Annual Report (Annual report, 2024)